14.1.3 Analyzing and interpreting data

• What does qualitative data describe?

  Qualities, characteristics, properties
• Qualitative data is best analyzed using statistical methods.

  False
• What is the purpose of tables in data representation?

  Organize and present data clearly
• The choice of data representation depends on the type of data
• Visual inspection can identify complex patterns in data.

  False
• What two factors determine the choice of data analysis technique?

  Type of data and complexity
• Descriptive statistics can identify non-linear relationships in data.

  False
• Time series analysis is effective for identifying temporal trends
• The mean is sensitive to outliers in a dataset.

  True
• The mode is useful for skewed or multimodal distributions
• What is the definition of absolute error?

  Measured minus true value
• What is the key difference between qualitative and quantitative data?

  Non-numerical vs. numerical
• Graphs are ideal for highlighting trends, patterns, and relationships
• Graphs effectively highlight trends but may obscure minor details
• What is a limitation of visual inspection for identifying trends and patterns?

  May miss subtle patterns
• Match the trend identification technique with its advantage:

  Visual Inspection ↔️ Simple and intuitive

  Descriptive Statistics ↔️ Quantifies central tendency

  Regression Analysis ↔️ Identifies linear relationships

  Time Series Analysis ↔️ Effective for temporal trends
• Statistical measures of central tendency summarize the typical value in a dataset.


  True
• Steps to follow when drawing conclusions from data:

  1️⃣ Restate the research question

  2️⃣ Summarize key findings

  3️⃣ Verify or refute the hypothesis

  4️⃣ Highlight statistical significance

  5️⃣ Discuss limitations and implications

  6️⃣ Suggest future research
• Statistical significance in quantitative data is determined using p-values or confidence intervals
• Match the data display method with its best use:

  Tables ↔️ Organizing qualitative data

  Graphs ↔️ Visualizing quantitative data
• Steps involved in communicating findings effectively:

  1️⃣ Use presentation techniques

  2️⃣ Create written reports
• Quantitative data is numerical information that can be measured and quantified
• Understanding the type of data is crucial for selecting the appropriate analysis techniques
• Graphs can become overwhelming for large datasets.

  False
• Why are graphs more appropriate for quantitative data than tables?

  Visualize trends and relationships
• Steps in identifying trends and patterns in data:

  1️⃣ Visual Inspection

  2️⃣ Descriptive Statistics

  3️⃣ Regression Analysis

  4️⃣ Time Series Analysis
• The choice of technique depends on the type of data and the complexity of the patterns
• Visual inspection is simple and intuitive but may miss subtle or complex patterns
• What is a disadvantage of regression analysis?

  Requires assumptions about data
• Which technique is recommended as a starting point for data analysis?

  Visual inspection
• Which measure of central tendency is robust to outliers?

  Median
• For what type of distribution is the mean the best measure of central tendency?

  Symmetric
• Relative error is expressed as a percentage
• Uncertainty propagation ensures the final result reflects the error in individual measurements.

  True
• Match the type of data with its characteristic:

  Qualitative Data ↔️ Non-numerical

  Quantitative Data ↔️ Numerical
• What is the primary purpose of graphs in data representation?

  Visualize relationships
• A line graph is better for observing seasonal temperature trends than a table.


  True
• Identifying trends and patterns in data is crucial for extracting meaningful insights
• The choice of technique depends on the type of data and the complexity of the patterns
• The mode may not be unique or representative.


  True